If you've ever watched a release slip because someone forgot to cherry-pick one commit onto the release branch, or spent an afternoon untangling why develop and main disagree about what's actually live, you've already run into this problem. The branching model usually gets blamed, but it's rarely the real issue — it's a mismatch between the strategy you copied and your actual deploy frequency, whether you need multiple versions live at once, and which manual steps nobody's gotten around to automating. Here's what I'd actually tell a team picking a branching strategy today, with the specifics that usually get skipped in the "GitFlow vs. trunk-based" comparisons. Deploy Frequency: The One Number That Decides Everything The branching debate isn't really about GitFlow vs. trunk-based philosophy — it's about how often you ship and how many versions need to be live simultaneously: Deploying daily or more fits trunk-based development...
Every few months someone asks me a version of the same question: "Should I just build my SaaS on AWS, or is that overkill for a small team?" The honest answer is: it depends less on AWS itself and more on the specific decisions you make on top of it — service selection, data modeling, cost controls, and where you deliberately choose not to over-engineer. Here's what I'd actually tell an engineering team building a SaaS product on AWS today, with the specifics that usually get skipped in the "10 AWS services for your startup" listicles. The Compute Layer: Pick Based on Execution Shape, Not Hype The Lambda-vs-containers debate isn't really about serverless philosophy — it's about execution shape: AWS Lambda fits short-lived, stateless, bursty work: API handlers, webhook processors, scheduled jobs. Watch two numbers: cold start latency (still meaningfully worse for Lambdas attached to a VPC, due to ENI creation — mitigated but not eliminate...